Automated Bug Discovery in Cloud Infrastructure-as-Code Updates with LLM Agents
Yiming Xiang, Zhenning Yang, Jingjia Peng, Hermann Bauer, Patrick Tser Jern Kon, Yiming Qiu, Ang Chen · 2025
Cloud environments are increasingly managed by Infrastructure-as-Code (IaC) platforms (e.g., Terraform), which allow developers to define their desired infrastructure as a configuration program that describes cloud resources and their dependencies. This shields developers from low-level operations for creating and maintaining resources, since they are automatically performed by IaC platforms when compiling and deploying the configuration. However, while IaC platforms are rigorously tested for initial deployments, they exhibit myriad errors for runtime updates, e.g., adding/removing resources and dependencies. IaC updates are common because cloud infrastructures are long-lived but user requirements fluctuate over time. Unfortunately, our experience shows that updates often introduce subtle yet impactful bugs. The update logic in IaC frameworks is hard to test due to the vast and evolving search space, which includes diverse infrastructure setups and a wide range of provided resources with new ones frequently added. We introduce TerraFault, an automated, efficient, LLM-guided system for discovering update bugs, and report our findings with an initial prototype. TerraFault incorporates various optimizations to navigate the large search space efficiently and employs techniques to accelerate the testing process. Our prototype has successfully identified bugs even in simple IaC updates, showing early promise in systematically identifying update bugs in today's IaC frameworks to increase their reliability.